[英]Is there an R spline that matches the Schoenberg algorithm?
Is there a R algorithm that fit smoothing splines while minimizing L,是否有 R 算法可以在最小化 L 的同时拟合平滑样条,
L = ρ ∑ (i from 0 to n-1) wi(yi-Si(xi))² + (1 - ρ) ∫ (x from 0 to x_(n-1)) (S''(x))² dx L = ρ ∑ (i from 0 to n-1) wi(yi-Si(xi))² + (1 - ρ) ∫ (x from 0 to x_(n-1)) (S''(x)) ² dx
Maybe it's possible with smooth.spline but I didn't succeed to find the good parameters.也许 smooth.spline 是可能的,但我没有成功找到好的参数。
(The equation can be seen more clearly here: https://www.iro.umontreal.ca/~simardr/ssj/doc/html/umontreal/iro/lecuyer/functionfit/SmoothingCubicSpline.html ) (这里的方程可以看的更清楚: https://www.iro.umontreal.ca/~simardr/ssj/doc/html/umontreal/iro/lecuyer/functionfit/SmoothingCubicSpline.html )
pspline::smooth.Pspline( x = input_x,
y = input_y,
norder = 2,
method = 1,
spar = rho)
will do the job.会做的工作。
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